DESCRIPTION: (Verbatim from the Applicant's Abstract) Development and clinical testing of an improved brain mapping and lesioning system is proposed. An improved MRI scan protocol, the intraoperative use of patient-specific MRI data and automation of major components of the microelectrode-guided neurosurgical procedure are key features of this system. These efforts are anticipated to improve the accuracy of lesion and/or deep brain stimulating electrode placement and to increase the efficiency and safety of this procedure. Increased usage and availability of this class of procedures is expected due to 'ease of use' characteristics achieved by automating many of the difficult and time consuming tasks. System development and enhancement will be based on the microelectrode-guided pallidotomy procedure pioneered at Emory University. A high resolution, high contrast MRI protocol will be developed for better visualization basal ganglia (BG) structures and greater spatial accuracy. It will be used to generate 3D mapping templates from patient-specific data volumes. Software for intra-operative useage will have the following functions: 1) automatic classification of neuronal discharge patterns and detection of BG nuclear boundaries, 2) automated detection of sensory-motor driving and visual evoked responses, 3) generation and co-registration of microelectrode trajectory plots with MRI incorporating data from 1 and 2, and 4) automated best-fit analysis to correlate recording track information with the MRI-based patient-specific MRI data volume. The system performance for neuronal pattern classification and BG nuclear boundary detection, sensory-motor driving and visual evoked response detection, microelectrode track generation, and track to template best-fit analysis will be compared individually to that of human experts. Upon achieving successful performance, a working prototype will be developed near the end of the second year that integrates these components and the clinical evaluation phase of the system will begin. Lesion accuracy, operating time, and a number of tracks required using the proposed system will be compared to similar data from procedures performed at Emory University using previous methods and technology.